000001815 001__ 1815
000001815 005__ 20160922104202.0
000001815 037__ $$aCTALK-2016-0001
000001815 100__ $$aVan Noten, Koen
000001815 245__ $$aTransfrontier macroseismic data exchange in NW Europe: examples of non-circular intensity distributions
000001815 260__ $$c2016
000001815 269__ $$c2016-05-21
000001815 520__ $$aMacroseismic data acquisition recently received a strong increase in interest due to public crowdsourcing through internet-based inquiries and real-time smartphone applications. Macroseismic analysis of felt earthquakes is important as the perception of people can be used to detect local/regional site effects in areas without instrumentation. We will demonstrate how post-processing macroseismic data improves the quality of real-time intensity evaluation of new events. Instead of using the classic DYFI representation in which internet intensities are averaged per community, we, first, geocoded all individual responses and structure the model area into 100 km2grid cells. Second, the average intensity of all answers within a grid cell is calculated. The resulting macroseismic grid cell distribution shows a less subjective and more homogeneous intensity distribution than the classical irregular community distribution and helps to improve the calculation of intensity attenuation functions. In this presentation, the ‘Did You Feel It’ (DYFI) macroseismic data of several >M4, e.g. the 2002 ML 4.9 Alsdorf and 2011 ML 4.3 Goch (Germany) and the 2015 ML 4.1 Ramsgate (UK), earthquakes felt in Belgium, Germany, The Netherlands, France, Luxemburg and UK are analysed. Integration of transfrontier DYFI data of the ROBBNS, KNMI, BCSF and BGS networks results in a particular non-circular, distribution of the macroseismic data in which the felt area for all these examples extends significantly more in E-W than N-S direction. This intensity distribution cannot be explained by geometrical amplitude attenuation alone, but rather illustrates a low-pass filtering effect due to the south-to-north increasing thickness of cover sediments above the London-Brabant Massif. For the studied M4 to M5 earthquakes, the thick sediments attenuate seismic energy at higher frequencies and consequently less people feel the vibrations at the surface. This example of successful macroseismic data exchange from multiple seismological institutions should encourage more seismological institutes to exchange macroseismic data more often, either in real-time or while postprocessing.
000001815 536__ $$aFNRS/$$cPDR/$$fT.0116.14
000001815 594__ $$aNO
000001815 6531_ $$aMacroseismology
000001815 6531_ $$aDid You Feel It?
000001815 6531_ $$amapping
000001815 6531_ $$aearthquake
000001815 700__ $$aLecocq, Thomas
000001815 700__ $$aHinzen, Klaus
000001815 700__ $$aSira, Christophe
000001815 700__ $$aCamelbeeck, Thierry
000001815 773__ $$tEGU GA, Vienna
000001815 8560_ $$fkoen.vannoten@observatoire.be
000001815 85642 $$ahttp://meetingorganizer.copernicus.org/EGU2016/EGU2016-4609.pdf
000001815 906__ $$aContributed
000001815 980__ $$aCTALKCONT